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PREDICTIVE ANALYTICS – How House of Cards Became a Monster Hit

House of Cards

Predictive analytics is the new competitive advantage and has fundamentally changed the way businesses compete and operate. The practice of extracting information from data sets in order to gain meaningful insights and improve business decisions has enabled a paradigm shift in how businesses predict future outcomes, and Netflix drama series HOUSE OF CARDS is a pretty good use case

House of Cards is an American political thriller web television drama series created by Beau Willimon. It is an adaptation of the 1990 BBC miniseries of the same title and based on the novel of the same title by Michael Dobbs. House of Cards has received positive reviews and several awards nominations which include 33 Primetime Emmy Award nominations and 8 Golden Globe Award nomination. It is by far my personal favourite when it comes to a TV drama series.

Netflix knew House of Card was going to be a mega hit even before the series was released.

How?

The American media-services provider headquartered in Los Gatos California which offer online streaming of a library of films and television programs had over 148 million paid subscriptions worldwide as at April 2019. Thanks to Big Data Analytics, Netflix knows what time of day movies are watched, it has records of why viewers pause, rewinds, and fast forward movies, it has ratings, searches and device type from millions of viewers and many more consumer or viewer based information. With regards to House of Cards:

  • Netflix knew millions of their viewers had searched and streamed the works of David Fincher. The producer of House of Cards.
  • Netflix also knew movies featuring Kelvin Spacey always did well. Spacey is an American actor, producer and singer who started his career as a stage actor during the 1980s
  • The British version of House of Cards had also done well. A 1990 British political thriller television serial in four episodes, set after the end of Margaret Thatcher’s tenure as Prime Minister of the United Kingdom.

Netflix also knew viewers who likes David Fincher also liked Kelvin Spacey

  • In a nutshell, Netflix knew and still knows what viewers want even before they did.

Today’s competitive economic environment is forcing companies to adopt innovative technology to boost performance. Below are some ways predictive analytics can be put to use:

1. Customer Relationship Management

Access an enhanced 360 view of customer no matter where that information resides. Integrating and streamlining customer data in a single system enable businesses to focus efforts on improving the relationship through communication, special offers, and regular engagement.

  • Sales and Marketing

Collecting and analyzing customer data, marketing teams can determine customer responses on purchases and optimize cross-selling and upselling opportunities, attracting and retaining profitable customers.

  • Price Optimization

Businesses can determine the direct relationship between demand and price for any product or service. Analytical pricing is being used in industries such as e-commerce, consumer goods, hospitality and air travel.

  • Fraud Detection

With behavioural analytics, predictable program eligibility and multiple detection methods, businesses are saving millions of dollars detecting fraud before it occurs. Banks, retailers, insurance providers are among early adopters.

  • Operations Management

Cutting cost and improving efficiency is key in a competitive environment such as ours today. Many organizations use predictive analytics tools to forecast inventory, manage resource and determine service capacity.

Using data to improve decision-making is affordable and accessible to businesses of all size. Regardless of your industry, you can use predictive analytics to improve functions and increase competitiveness. There are solutions for companies of all sizes, including free tools. However, only a handful deliver on the promise and that’s where you trust experts.

To integrate predictive analytics in your business process or you’d like to gain knowledge and expertise in Data Analytics, contact us at Eureka Labs today.

Uko George is a Technical Business Analyst with over 10 year’s hands-on work experience in the fields of Telecommunication, Business Development, and Data Analytics. A Google certified Analytics Expert, Certified Trainer for Facebook, and proficient in IBM Watson for Data Science Solution. He is the co-founder at Eureka Labs.  

Facebook | Instagram | LinkedIn | Twitter : EMAIL: ukogeorge@eureka.com.ng | eurekamails@gmail.com

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